
Before mathematical models were used in neuroscience, models have mainly been limited to imprecise word models. Such word models that have sounded reasonable in the past have turned out to be inconsistent and unworkable when trying to convert to a mathematical model [Abbott]. Simulation enables precise models to be tested on large interconnected networks. The proposed language Synapse is a language specifically for modeling and simulating neural networks.

While every neuron in the brain executes in parallel, most languages are written for architectures that execute sequential. Even as parallel computing becomes more important, parallel support is usually added as an after-thought. For example, CUDA relies on extending C and C++ so that it can take advantage of nVidia's graphic cards and OpenMP adds C preprocessor commands to enable, among other things, parallel for-loops.
Synapse is a language that being created for parallel execution from the ground up.

The source code and documentation (including the LaTeX source for PDFs) may be downloaded from
\url{http://synapse-lang.googlecode.com}.